A Distributed Computing Platform Supporting Power System Security Knowledge Discovery Based on Online Simulation

Huang, Tianen; Guo, Qinglai; Sun, Hongbin

doi:10.1109/tsg.2016.2571442

Cited by 37 publications

(13 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, to help dealing with a massive amount of data, in [25], the authors propose a distributed computing platform for data sampling, feature selection, knowledge discovery and online security analysis.…”

Section: A Database Buildingmentioning

confidence: 99%

Recent Developments in Machine Learning for Energy Systems Reliability Management

2020

View full text Add to dashboard Cite

This paper reviews recent works applying machine learning techniques in the context of energy systems reliability assessment and control. We showcase both the progress achieved to date as well as the important future directions for further research, while providing an adequate background in the fields of reliability management and of machine learning. The objective is to foster the synergy between these two fields and speed up the practical adoption of machine learning techniques for energy systems reliability management. We focus on bulk electric power systems and use them as an example, but we argue that the methods, tools, etc. can be extended to other similar systems, such as distribution systems, micro-grids, and multi-energy systems.

show abstract

Section: A Database Buildingmentioning

confidence: 99%

Recent Developments in Machine Learning for Energy Systems Reliability Management

2020

View full text Add to dashboard Cite

show abstract

“…Graph theory is widely used in the vulnerability analysis [8]. There are many software libraries for working on large graphs [21]. Some of them are implemented on the basis of parallel and distributed computations [22].…”

Section: High-performance Computing In Studying Energy System Resiliencementioning

confidence: 99%

“…The study and analysis of the energy system adaptation and recovery capabilities is usually implemented on the basis of mathematical optimization packages [23], which have built-in tools for organizing high-performance computing. In studying energy system resilience, parallel computations are mainly used for calculating large optimization tasks, such as an energy distribution over real energy system networks [16,21] or resource allocation when planning an energy system recovery. Distributed computing is used in vulnerability analysis, where problems are mostly combinatorial in nature, and their solution is quite easily scaled.…”

Section: High-performance Computing In Studying Energy System Resiliencementioning

confidence: 99%

Application of high-performance computing for determining critical components of an energy system

et al. 2020

View full text Add to dashboard Cite

This article presents a package for analyzing the energy system vulnerability developed with new technology for continuous integration, delivery, and deployment of applied software. It implements a framework that allows combining and optimally using various methods for modelling energy systems and provides the comprehensive assessment of their vulnerability with regard to various uncertainties. The essential principles to identify and rank critical elements of an energy system are considered in the article. The investigations made with the package shown that the principles seem to be logical for the subsequent construction of the invariant set of measures for improving the energy system resilience.

show abstract

“…Fusing can be done in multimodal non-invasive biometrics in real time to secure IoT industries. Tian-en Huang et al [47] Distributed Computing Platform Supporting Power System Security Knowledge Discovery Based on Online Simulation.…”

Section: Lucas Silvamentioning

confidence: 99%

CCTV Surveillance System, Attacks and Design Goals

Muthusenthil¹,

Kim²

2018

IJECE

View full text Add to dashboard Cite

Closed Circuit Tele-Vision surveillance systems are frequently the subject of debate. Some parties seek to promote their benefits such as their use in criminal investigations and providing a feeling of safety to the public. They have also been on the receiving end of bad press when some consider intrusiveness has outweighed the benefits. The correct design and use of such systems is paramount to ensure a CCTV surveillance system meets the needs of the user, provides a tangible benefit and provides safety and security for the wider law-abiding public. In focusing on the normative aspects of CCTV, the paper raises questions concerning the efficiency of understanding contemporary forms of ‘social ordering practices’ primarily in terms of technical rationalities while neglecting other, more material and ideological processes involved in the construction of social order. In this paper, a 360-degree view presented on the assessment of the diverse CCTV video surveillance systems (VSS) of recent past and present in accordance with technology. Further, an attempt been made to compare different VSS with their operational strengths and their attacks. Finally, the paper concludes with a number of future research directions in the design and implementation of VSS.

show abstract

A Distributed Computing Platform Supporting Power System Security Knowledge Discovery Based on Online Simulation

Cited by 37 publications

References 19 publications

Recent Developments in Machine Learning for Energy Systems Reliability Management

Recent Developments in Machine Learning for Energy Systems Reliability Management

Application of high-performance computing for determining critical components of an energy system

CCTV Surveillance System, Attacks and Design Goals

Contact Info

Product

Resources

About